MIMO Channel Prediction using Recurrent Neural Networks

Abstract

Adaptive modulation is a communication technique capable of maximizing throughput while guaranteeing a fixed symbol error rate (SER). However, this technique requires instantaneous channel state information at the transmitter. This can be obtained by predicting channel states at the receiver and feeding them back to the trasnmitter. Existing algorithms used to predict single-input single-output (SISO) channels with recurrent neural networks (RNN) are extended to multiple-input multiple-output (MIMO) channels for use with adaptive modulation and their performance is demonstrated in several examples. © International Foundation for Telemetering, 2008.

Department(s)

Electrical and Computer Engineering

Keywords and Phrases

Adaptive modulation; Channel prediction; Flat fading; Multiple-input multiple-output (MIMO); Online training; Recurrent neural networks

International Standard Serial Number (ISSN)

0884-5123

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 International Foundation for Telemetering, All rights reserved.

Publication Date

01 Dec 2008

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